Software Engineer, Nominal

• 5+ years of experience building AI or machine learning products that shipped to production
• Experience working with large datasets, time series data, observability platforms, data infrastructure, or machine learning systems
• A background in ML, data science, applied AI, or adjacent fields that gives you strong intuition for working with data-intensive systems
• Strong software engineering fundamentals, with experience designing scalable backend or distributed systems
• Experience taking products from zero-to-one, whether at a startup or inside an entrepreneurial team within a larger company
• Strong product instincts and curiosity about customer problems
• Prior startup founding experience or experience on an incubation/new products team

Desirable

• We're looking for an experienced software engineer to join our Hardware Intelligence team. This is a highly ambiguous, zero-to-one engineering role. You'll build the infrastructure, data systems, and AI capabilities that power the next generation of intelligent engineering tools
• Rather than implementing predefined product requirements, you'll work alongside customers and product leaders to discover what should exist, and then build it
• Success in this role comes from being comfortable making technical bets, rapidly prototyping new ideas, and turning uncertainty into working software
• Build the systems that power Hardware Intelligence, including agent infrastructure, evaluation pipelines, retrieval systems, and tooling for reasoning over engineering data
• Design and ship AI-powered workflows that help engineers investigate anomalies, perform root cause analysis, and understand complex hardware behavior
• Work across large-scale time series, telemetry, logs, and other engineering datasets to build robust, production-ready systems
• Prototype new approaches quickly, evaluate them with customers, and iterate based on real-world feedback
• Partner closely with engineers and product leaders to determine where the team should invest next
• Help establish engineering patterns, infrastructure, and best practices as Hardware Intelligence scales
• Engage directly with customers to understand how complex engineering problems are solved today and translate those workflows into product capabilities